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. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also expected
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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to build more trustworthy and robust AI models that can address domain-specific challenges in biomedical applications. The PhD project will focus on translating and enhancing cutting-edge algorithms from AI
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positioning, navigation, and timing (PNT) applications for the next generation satellite systems Developing innovative solutions and algorithms to integrate communication and sensing or communications and PNT
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to build a distributed and cooperative network. To develop signal processing techniques, the group researchers use real data captured by available radar modules at the lab or custom-built MIMO radar with
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of public data. Key challenges include balancing privacy guarantees with utility, designing efficient algorithms for real-world applications, and assessing security and business implications in practical
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the opportunity to investigate a broad range of research areas with particular focus on understanding the foreseeable adoption of various energy technologies related to e-mobility (e.g., distributed
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use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group